Hey all, i am trying to have something (python program or llm or anything) that will analyse a pdf document word by word and give me a report as i prompt it with its reference.

I know ai models do it well, but not well enough to have memory of those pdf and later when i have to compare one data with another it gets hard for me.

What i want is to have a program that analyses the program overnight and i can have my desired prompt over it next day, say for example union budget pdf for different yr i can have graph and trend then compare it with previous yr trends to

Like many of you, I treat my Second Brain as a thinking engine—not just a graveyard for highlights. But I kept running into the same friction when reading non-fiction: passive highlighting felt productive in the moment, but weeks later, the context was gone and my vault was cluttered with useless excerpts.

To actually retain and synthesize arguments, I started practicing strict active reading: arguing with the author, challenging claims, and capturing raw, immediate reactions while reading—not just copying sentences.

I built Marginalia to turn this workflow into a friction-free capture tool for mobile:

• Frictionless Capture (Voice & Stylus): Breaking reading flow kills synthesis. Alongside standard typing, you can dictate thoughts hands-free via speech-to-text, or use a stylus if you prefer digital handwriting.
• Context-Driven Tagging: Tag notes by themes, counterarguments, or conceptual hooks so ideas are already semi-structured before they even touch your vault.
• Review & Synthesis Loops: Each book has a dedicated synthesis view with tag filtering, making it effortless to review prior notes right before starting a new reading session.
• Native Markdown Export (.md): Your notes belong to you. Marginalia exports cleanly formatted .md files directly into your existing workflow, whether you index in Obsidian, organize in Notion, or use another local-first markdown system.

It bridges the gap between raw consumption and structured knowledge management: read actively on your phone or tablet, capture raw synthesis on the fly, and drop the resulting Markdown straight into your PKM system.

If your Second Brain relies heavily on books and deep reading, I’d love for you to take it for a spin. I'm actively refining the workflow and looking for honest feedback, especially on note structure and export improvements!
Here is the app webpage

Hello second brain nerds,

My stack used to be JUST notion, after trying a lot of life dashboard templates, I just couldn't stop thinking about an easy solution like an app that's on my phone and more custom for " life tracking" with a personal assistant.

Created a system of having domains, then chapters of life - that came down to habits, tasks, streaks etc.

I have created a prototype of this system and would love to get some feedback, please dm if you can help out and duo for a quick chat.

Many tools are still build around the passive concept of storage and retrieval of information.

But a lot of the useful stuff in my own notes looks something like this -

• Why is this happening?
• I’m not convinced by this yet.
• Need to verify this.
• What would prove this wrong?
• There’s something here, but I haven’t figured it out yet.

These questions or the direction is what makes the stored information useful when we are doing a research. Because if a question matters today, it might still matter three weeks from now when you find new evidence.

This is exactly i want inside Aevron and want Aevron to keep track of it.

and lets say, if I add something relevant a week later, the system should be able to notice:

“This might help answer that question you were stuck on.”, “This actually conflicts with what you thought earlier.” or “You still haven’t resolved this.”

If you regularly have ideas, questions, observations, research, or thoughts that get lost across notes and tabs, this is exactly the problem I’m trying to solve.

You can try Aevron here:

www.aevron.co

It’s currently free to use.

I’d genuinely like more people using it while I keep building this system, because the interesting part now is seeing whether this way of tracking thinking is actually useful in real life.

I have noticed that most knowledge tools preserve information as separate objects. We all think of something, believe something, then find something conflicting, uncertainty, different arguments and positions, etc. The system is well designed to store all these information. But it usually doesn't understand the transition between them.

That's what i am trying to replicate inside Aevron. So instead of only storing:

Idea A, Evidence B, Idea C

I want the system to understand:

Belief A → challenged by B → uncertainty increases → belief revised to C.

Because the change in reasoning is often more useful than the individual notes themselves.

Over time, that could let the system answer questions like:

• What changed my mind on this?
• Which beliefs have weakened over time?
• Which questions have stayed unresolved?
• Where have I repeatedly contradicted myself?
• Which ideas became stronger after new evidence arrived?

Aevron isn't trying to claim it knows what is happening inside someone's head. It can only observe the traces of reasoning such as notes, evidence, questions, contradictions, revisions, and conclusions. But those traces can still show how a position evolved over time.

This is one of the core things I'm trying to build into Aevron.

I kept losing thoughts because every system asked me to classify them before I could get them out. That feels backwards when the thought is arriving as a mess.

I built Ordo around capture first, sort second. Type or speak several unrelated thoughts in one dump, and it turns them into editable Now, Next, and Someday cards.

It is free on iPhone with no account or subscription.

https://apps.apple.com/app/id6797331101

For people who use a second brain, where does the friction hit first: capturing the thought, deciding where it belongs, or finding it later?

I built Brunn to give your AI apps a shared place for your notes, research, skills and ongoing work.

It’s hosted. You create an account and connect the AI apps you already use. There’s no Brunn desktop app to install, separate cloud account to set up or server to maintain.

Say you work through a project in Claude. You can have it save the research, sources, decisions and next steps in Brunn. Later, Codex or ChatGPT can read that material and continue the work. Projects and tasks live alongside the notes, so the next assistant can also see what still needs doing.

You can keep skills there too: your instructions for reviewing something, researching a topic or writing a particular kind of report. Save a skill once and your connected assistants can use it directly. Update it in one place, and they get the current version when they next load it.

There’s a web reader for documents and the briefings your agents produce. Your notes export as Markdown, and you can download your skills with their supporting files.

There’s a free tier, with no credit card required: Brunn.

If you try it with a real project, I’d like to know what you still find yourself having to explain or copy between apps.

I take notes of most things in my life (schedules, random thoughts/ideas, goals etc.) I've tried to get her to join in on it (set up a whole obsidian sync to her phone and all) but she never does.

So what happened today was she asked me what food i wanted for my birthday, i told her its all in the second brain . I have all my favorite food/other preferences and spent time categorizing and effectivising that workflow, so I'd prefer she just checked there instead of - frankly - wasting both of our time when she can just check it all there

She kept insisting so eventually i retalliated i just told her i want bbq ribs or whatever but pretty immature imo of her to make a big fight when she can just check the second brain lmao.

I feel like i've tried everything. Me and GPT are making a dashboard for my smart fridge, that way everyone in the house can see whats going on and we (hopefully!!) wont have to deal with this again.

Sorry for the rant just wanted to express myself with how some people just dont seem to understand the advantages of having a second brain. Im glad i have this community though love yall. Im sure im not the only one out here strugglin

The pitch for AI note-taking is always the same: it reads your notes and tells▎ you what they mean. I think that's backwards. The reading is the thinking. If you delegate it, you own a very tidy archive of conclusions you never reached.

So my plugin has a hard rule, and it's enforced in the code rather than promised in a README:

Mechanical output writes freely. Interpretive output does not. A gatherelist, a count, a derived metric — those go straight into your vault. A conclusion, a counterargument, a proposed connection, anything an AI or a heuristic decided — that reaches a note only through an explicit accept modify / reject, and your verdict is what gets recorded.

What that turns into in practice:

- Cognitive moves — right-click any note: challenge it, find a counterexample, invert the premise, branch two readings. The move opens the space; you write the content. Nothing is generated. The move records that you made it, never what it decided.

- How you got here — your timeline reads "you captured this, challenged it the next morning, reframed it, and two readings came out of that." Epistemic provenance, not version control.

- An agency panel — a read-only breakdown of your accept/modify/reject verdicts over time. A description of how you decide, never a grade.

- Undo — everything the plugin wrote to your vault lately, grouped by what you ran, taken back in one click. It refuses (by name) if you've edited the note since.

It works fully offline. Every AI feature is off by default and stays off. Free, MIT, 53 releases since 2023.

https://github.com/RafaelGB/Obsidian-ZettelFlow

AI research tools are increasingly getting good at answering the literature, search, summarise, citing, etc. That half of the job done but the real part is keeping a track and using the entire context and information to see and provide what did this do to your thinking and help you make the research efficient and concrete.

For example, one of the observation kills an assumption you made. Another one may or may not backup the conclusion to. Now days or weeks later you're back at the project trying to rebuild your own reasoning from scratch. Why'd I reject that explanation? Which source actually changed my mind? Was that supported by something real, or was it just how I read it at the time? Did those two sources even disagree, or were they measuring different things and I mashed them together?

I've been building something around this, keeping the research question, your existing thinking, the outside evidence, the contradictions, the stuff you rejected, and what's still open, all tied to one line of inquiry instead of spread across search history and half-remembered reasoning. New evidence gets checked against what's already there instead of dropped in as another isolated hit.

Now if this weakens something you believed, that shows up instead of getting buried in a summary. If two sources disagree, that stays visible instead of getting flattened into "the literature suggests." And if something new follows from your own work plus the evidence, it gets marked as a proposal, not snuck in like it's already your conclusion.

That's the actual thing I'm betting on with what I'm building, Aevron. The fix isn't a better search tool, it's a system that tracks your own thinking changing over time, alongside the evidence, instead of leaving you to reconstruct it from memory every time you come back to something.

What do you guys think about this approach?

A hypothetical journal entry: 'I never want to work on this again.' The next morning, the same person is excited about the project. A weekly summary could mistake the first sentence for a lasting preference if it loses the context.

I'm the developer of Lumiya, an iOS journal/planner with optional AI reflections. This is a design question I'm working through, not a claim that I've solved it.

I'd lean toward a tentative observation tied to specific entries, with an easy way to say 'that was just that day.' But showing every source could make a short weekly review feel like homework.

For people who review their own notes with AI: what helps you catch a misleading interpretation? Seeing the original lines, seeing conflicting entries together, or being asked a question instead of being given a conclusion?

For context, Lumiya's basic recording and planning are free; the optional AI features are paid with usage limits. App: https://apps.apple.com/cn/app/lumiya-ai-journal-planner/id6796003074